The present disclosure relates generally to a three-dimensional (3-D) vessel tree surface reconstruction method, particularly to a 3-D coronary artery tree surface reconstruction method, and more particularly to a 3-D coronary artery tree surface reconstruction method from a limited number of two-dimensional (2-D) rotational X-ray angiography images.
In percutaneous coronary intervention (PCI) procedures, physicians evaluate and identify coronary artery lesion (stenosis), and prepare catheterization utilizing X-Ray coronary angiographic images. These images are 2-D projection images of a complex coronary artery tree acquired by X-Ray machines called C-Arms either from bi-plane or from mono-plane detector arrangements. 2-D projections cause vessel occlusion, crossing, and foreshortening. To better understand vessel geometry, multiple views with different angles may be acquired. In addition, 2-D projection image based quantitative coronary analysis (QCA) may determine lesion length and stent size during PCI. However, there are two major limitations of 2-D QCA: foreshortening and out-of-plane magnification errors.
3-D reconstruction of the vessel surface may be used to avoid the limitations of 2-D QCA. In some 3-D tomographic reconstructions of coronary arteries, motion artifact is minimized through a pre-computed 4-D motion field. The 4-D motion field is computed from 3-D coronary artery centerline reconstruction and a 4-D parametric motion model fitting. However, this tomographic-based approach is computationally expensive. In addition, using a limited number of images can cause a blur and low resolution reconstruction. In another approach, 3-D symbolic reconstruction uses two projections and multiple projections. A 3-D vessel skeleton is reconstructed, and then an elliptical model representing a vessel cross-section is fit using 2-D measurement (e.g. segmentation) or estimating vessel radii from 2-D measurement. Different centerline reconstruction approaches are used without computationally expensive surface reconstruction. Elliptical or circular models are symbolic and are not accurate due to lumen deformation and lesion. 2-D vessel lumen segmentation on the projection image is a challenging task due to vessel occlusion and crossing, so may require many iterations of user intervention.
U.S. Published Application No. 2017-0018116 discloses automatic generation of a 3-D vessel geometry for performing 3-D QCA in PCI procedures. Generation of the 3-D vessel geometry without full surface reconstruction may avoid the limitations from 2-D projection images. 3-D QCA allows quantitative determination of vessel lumen, grade of stenosis, and non-invasive calculation of fractional flow reserve (FFR). Rigid cardiac motion in ECG synchronized frames is assumed. The surface fit may be less accurate than desired in some cases.